期刊
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
卷 100, 期 469, 页码 286-295出版社
AMER STATISTICAL ASSOC
DOI: 10.1198/016214504000001015
关键词
balance; generalized linear model; inner product scaling; social network
This article discusses the use of asymmetric multiplicative interaction effect to capture certain types of third-order dependence patterns often present in social networks and other dyadic datasets. Such an effect, along with standard linear fixed and random effects, is incorporated into a generalized linear model, and a Markov chain Monte Carlo algorithm is provided for Bayesian estimation and inference. In an example analysis of international relations data, accounting for such patterns improves model fit and predictive performance.
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